Pandas Profiling Report

Dataset statistics

Number of variables	13
Number of observations	1000
Missing cells	74
Missing cells (%)	0.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	97.8 KiB
Average record size in memory	100.1 B

Variable types

DateTime	1
Numeric	2
Text	9
Categorical	1

Alerts

`salary` has 68 (6.8%) missing values	Missing
`id` is uniformly distributed	Uniform
`id` has unique values	Unique
`ip_address` has unique values	Unique

Reproduction

Analysis started	2024-10-29 02:38:32.846633
Analysis finished	2024-10-29 02:38:34.448124
Duration	1.6 second
Software version	ydata-profiling vv4.11.0
Download configuration	config.json

registration_dttm
Date

Distinct	995
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Minimum	2016-02-03 00:01:00
Maximum	2016-02-03 23:59:55

Histogram with fixed size bins (bins=50)

id
Real number (ℝ)

Uniform Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	500.5

Minimum	1
Maximum	1000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.0 KiB

Quantile statistics

Minimum	1
5-th percentile	50.95
Q1	250.75
median	500.5
Q3	750.25
95-th percentile	950.05
Maximum	1000
Range	999
Interquartile range (IQR)	499.5

Descriptive statistics

Standard deviation	288.81944
Coefficient of variation (CV)	0.57706181
Kurtosis	-1.2
Mean	500.5
Median Absolute Deviation (MAD)	250
Skewness	0
Sum	500500
Variance	83416.667
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1000	1	0.1%
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%
6	1	0.1%
7	1	0.1%
961	1	0.1%
962	1	0.1%
Other values (990)	990	99.0%

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%
6	1	0.1%
7	1	0.1%
8	1	0.1%
9	1	0.1%
10	1	0.1%

Value	Count	Frequency (%)
1000	1	0.1%
999	1	0.1%
998	1	0.1%
997	1	0.1%
996	1	0.1%
995	1	0.1%
994	1	0.1%
993	1	0.1%
992	1	0.1%
991	1	0.1%

first_name
Text

Distinct	198
Distinct (%)	19.8%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	11
Median length	10
Mean length	5.639
Min length	0

Characters and Unicode

Total characters	5639
Distinct characters	45
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	13 ?
Unique (%)	1.3%

Sample

1st row	Amanda
2nd row	Albert
3rd row	Evelyn
4th row	Denise
5th row	Carlos

Value	Count	Frequency (%)
samuel	11	1.1%
peter	11	1.1%
mark	11	1.1%
cheryl	10	1.0%
stephen	10	1.0%
marie	10	1.0%
jack	10	1.0%
dennis	10	1.0%
norma	10	1.0%
alice	9	0.9%
Other values (187)	882	89.6%

Most occurring characters

Value	Count	Frequency (%)
a	631	11.2%
e	610	10.8%
n	457	8.1%
r	436	7.7%
i	409	7.3%
l	319	5.7%
h	268	4.8%
o	262	4.6%
t	222	3.9%
y	194	3.4%
Other values (35)	1831	32.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5639	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	631	11.2%
e	610	10.8%
n	457	8.1%
r	436	7.7%
i	409	7.3%
l	319	5.7%
h	268	4.8%
o	262	4.6%
t	222	3.9%
y	194	3.4%
Other values (35)	1831	32.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5639	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	631	11.2%
e	610	10.8%
n	457	8.1%
r	436	7.7%
i	409	7.3%
l	319	5.7%
h	268	4.8%
o	262	4.6%
t	222	3.9%
y	194	3.4%
Other values (35)	1831	32.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5639	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	631	11.2%
e	610	10.8%
n	457	8.1%
r	436	7.7%
i	409	7.3%
l	319	5.7%
h	268	4.8%
o	262	4.6%
t	222	3.9%
y	194	3.4%
Other values (35)	1831	32.5%

last_name
Text

Distinct	247
Distinct (%)	24.7%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	10
Median length	9
Mean length	6.093
Min length	3

Characters and Unicode

Total characters	6093
Distinct characters	46
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	13 ?
Unique (%)	1.3%

Sample

1st row	Jordan
2nd row	Freeman
3rd row	Morgan
4th row	Riley
5th row	Burns

Value	Count	Frequency (%)
barnes	10	1.0%
willis	9	0.9%
shaw	9	0.9%
patterson	9	0.9%
lane	8	0.8%
henderson	8	0.8%
gonzalez	8	0.8%
dixon	8	0.8%
jackson	8	0.8%
medina	8	0.8%
Other values (237)	915	91.5%

Most occurring characters

Value	Count	Frequency (%)
e	663	10.9%
r	559	9.2%
n	521	8.6%
a	451	7.4%
o	426	7.0%
l	391	6.4%
s	388	6.4%
i	323	5.3%
t	209	3.4%
d	165	2.7%
Other values (36)	1997	32.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6093	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	663	10.9%
r	559	9.2%
n	521	8.6%
a	451	7.4%
o	426	7.0%
l	391	6.4%
s	388	6.4%
i	323	5.3%
t	209	3.4%
d	165	2.7%
Other values (36)	1997	32.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6093	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	663	10.9%
r	559	9.2%
n	521	8.6%
a	451	7.4%
o	426	7.0%
l	391	6.4%
s	388	6.4%
i	323	5.3%
t	209	3.4%
d	165	2.7%
Other values (36)	1997	32.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6093	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	663	10.9%
r	559	9.2%
n	521	8.6%
a	451	7.4%
o	426	7.0%
l	391	6.4%
s	388	6.4%
i	323	5.3%
t	209	3.4%
d	165	2.7%
Other values (36)	1997	32.8%

email
Text

Distinct	985
Distinct (%)	98.5%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	32
Median length	28
Mean length	20.632
Min length	0

Characters and Unicode

Total characters	20632
Distinct characters	39
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	984 ?
Unique (%)	98.4%

Sample

1st row	ajordan0@com.com
2nd row	afreeman1@is.gd
3rd row	emorgan2@altervista.org
4th row	driley3@gmpg.org
5th row	cburns4@miitbeian.gov.cn

Value	Count	Frequency (%)
jberryc@usatoday.com	1	0.1%
dhudsone@blogger.com	1	0.1%
bwillisf@bluehost.com	1	0.1%
eandrewsg@cornell.edu	1	0.1%
swallaceh@netvibes.com	1	0.1%
clawsoni@vkontakte.ru	1	0.1%
rbellj@bandcamp.com	1	0.1%
dstevensk@cnet.com	1	0.1%
lramosl@sourceforge.net	1	0.1%
gbarnesm@google.ru	1	0.1%
Other values (974)	974	99.0%

Most occurring characters

Value	Count	Frequency (%)
o	1808	8.8%
e	1544	7.5%
c	1289	6.2%
a	1233	6.0%
r	1188	5.8%
m	1173	5.7%
n	1094	5.3%
.	1071	5.2%
s	1005	4.9%
@	984	4.8%
Other values (29)	8243	40.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	20632	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	1808	8.8%
e	1544	7.5%
c	1289	6.2%
a	1233	6.0%
r	1188	5.8%
m	1173	5.7%
n	1094	5.3%
.	1071	5.2%
s	1005	4.9%
@	984	4.8%
Other values (29)	8243	40.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	20632	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	1808	8.8%
e	1544	7.5%
c	1289	6.2%
a	1233	6.0%
r	1188	5.8%
m	1173	5.7%
n	1094	5.3%
.	1071	5.2%
s	1005	4.9%
@	984	4.8%
Other values (29)	8243	40.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	20632	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	1808	8.8%
e	1544	7.5%
c	1289	6.2%
a	1233	6.0%
r	1188	5.8%
m	1173	5.7%
n	1094	5.3%
.	1071	5.2%
s	1005	4.9%
@	984	4.8%
Other values (29)	8243	40.0%

gender
Categorical

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Female	482
Male	451
	67

Length

Max length	6
Median length	4
Mean length	4.696
Min length	0

Characters and Unicode

Total characters	4696
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Female
2nd row	Male
3rd row	Female
4th row	Female
5th row

Common Values

Value	Count	Frequency (%)
Female	482	48.2%
Male	451	45.1%
	67	6.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
female	482	51.7%
male	451	48.3%

Most occurring characters

Value	Count	Frequency (%)
e	1415	30.1%
a	933	19.9%
l	933	19.9%
F	482	10.3%
m	482	10.3%
M	451	9.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4696	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1415	30.1%
a	933	19.9%
l	933	19.9%
F	482	10.3%
m	482	10.3%
M	451	9.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4696	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1415	30.1%
a	933	19.9%
l	933	19.9%
F	482	10.3%
m	482	10.3%
M	451	9.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4696	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1415	30.1%
a	933	19.9%
l	933	19.9%
F	482	10.3%
m	482	10.3%
M	451	9.6%

ip_address
Text

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	15
Median length	14
Mean length	13.289
Min length	8

Characters and Unicode

Total characters	13289
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	1.197.201.2
2nd row	218.111.175.34
3rd row	7.161.136.94
4th row	140.35.109.83
5th row	169.113.235.40

Value	Count	Frequency (%)
239.182.219.189	1	0.1%
217.1.147.132	1	0.1%
1.197.201.2	1	0.1%
218.111.175.34	1	0.1%
7.161.136.94	1	0.1%
140.35.109.83	1	0.1%
169.113.235.40	1	0.1%
195.131.81.179	1	0.1%
143.232.204.137	1	0.1%
99.102.42.63	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
.	3000	22.6%
1	2504	18.8%
2	1702	12.8%
4	913	6.9%
3	871	6.6%
5	852	6.4%
0	703	5.3%
9	699	5.3%
8	690	5.2%
7	687	5.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13289	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	3000	22.6%
1	2504	18.8%
2	1702	12.8%
4	913	6.9%
3	871	6.6%
5	852	6.4%
0	703	5.3%
9	699	5.3%
8	690	5.2%
7	687	5.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13289	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	3000	22.6%
1	2504	18.8%
2	1702	12.8%
4	913	6.9%
3	871	6.6%
5	852	6.4%
0	703	5.3%
9	699	5.3%
8	690	5.2%
7	687	5.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13289	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	3000	22.6%
1	2504	18.8%
2	1702	12.8%
4	913	6.9%
3	871	6.6%
5	852	6.4%
0	703	5.3%
9	699	5.3%
8	690	5.2%
7	687	5.2%

cc
Text

Distinct	710
Distinct (%)	71.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	19
Median length	18
Mean length	11.409
Min length	0

Characters and Unicode

Total characters	11409
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	709 ?
Unique (%)	70.9%

Sample

1st row	6759521864920116
2nd row
3rd row	6767119071901597
4th row	3576031598965625
5th row	5602256255204850

Value	Count	Frequency (%)
3583136326049310	1	0.1%
30475362189761	1	0.1%
5100143489438123	1	0.1%
3582151311470687	1	0.1%
3573030625927601	1	0.1%
3548019978887852	1	0.1%
375696484097714	1	0.1%
3554329250601579	1	0.1%
5020868434918236	1	0.1%
30392894850853	1	0.1%
Other values (699)	699	98.6%

Most occurring characters

Value	Count	Frequency (%)
5	1444	12.7%
3	1416	12.4%
6	1155	10.1%
0	1134	9.9%
4	1107	9.7%
2	1077	9.4%
7	1074	9.4%
1	1051	9.2%
8	994	8.7%
9	957	8.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11409	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
5	1444	12.7%
3	1416	12.4%
6	1155	10.1%
0	1134	9.9%
4	1107	9.7%
2	1077	9.4%
7	1074	9.4%
1	1051	9.2%
8	994	8.7%
9	957	8.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11409	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
5	1444	12.7%
3	1416	12.4%
6	1155	10.1%
0	1134	9.9%
4	1107	9.7%
2	1077	9.4%
7	1074	9.4%
1	1051	9.2%
8	994	8.7%
9	957	8.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11409	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
5	1444	12.7%
3	1416	12.4%
6	1155	10.1%
0	1134	9.9%
4	1107	9.7%
2	1077	9.4%
7	1074	9.4%
1	1051	9.2%
8	994	8.7%
9	957	8.4%

country
Text

Distinct	120
Distinct (%)	12.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	32
Median length	22
Mean length	7.507
Min length	4

Characters and Unicode

Total characters	7507
Distinct characters	51
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	37 ?
Unique (%)	3.7%

Sample

1st row	Indonesia
2nd row	Canada
3rd row	Russia
4th row	China
5th row	South Africa

Value	Count	Frequency (%)
china	189	17.2%
indonesia	97	8.8%
russia	62	5.6%
philippines	45	4.1%
brazil	38	3.5%
portugal	38	3.5%
france	37	3.4%
poland	35	3.2%
sweden	25	2.3%
japan	20	1.8%
Other values (131)	515	46.8%

Most occurring characters

Value	Count	Frequency (%)
a	1076	14.3%
i	851	11.3%
n	836	11.1%
e	536	7.1%
s	361	4.8%
o	342	4.6%
r	309	4.1%
h	297	4.0%
l	295	3.9%
d	262	3.5%
Other values (41)	2342	31.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7507	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	1076	14.3%
i	851	11.3%
n	836	11.1%
e	536	7.1%
s	361	4.8%
o	342	4.6%
r	309	4.1%
h	297	4.0%
l	295	3.9%
d	262	3.5%
Other values (41)	2342	31.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7507	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	1076	14.3%
i	851	11.3%
n	836	11.1%
e	536	7.1%
s	361	4.8%
o	342	4.6%
r	309	4.1%
h	297	4.0%
l	295	3.9%
d	262	3.5%
Other values (41)	2342	31.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7507	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	1076	14.3%
i	851	11.3%
n	836	11.1%
e	536	7.1%
s	361	4.8%
o	342	4.6%
r	309	4.1%
h	297	4.0%
l	295	3.9%
d	262	3.5%
Other values (41)	2342	31.2%

birthdate
Text

Distinct	788
Distinct (%)	78.8%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	27
Median length	10
Mean length	7.222
Min length	0

Characters and Unicode

Total characters	7222
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	771 ?
Unique (%)	77.1%

Sample

1st row	3/8/1971
2nd row	1/16/1968
3rd row	2/1/1960
4th row	4/8/1997
5th row

Value	Count	Frequency (%)
12/12/1983	2	0.2%
10/7/1986	2	0.2%
11/18/1958	2	0.2%
4/10/1965	2	0.2%
7/21/1986	2	0.2%
10/5/1982	2	0.2%
11/25/1998	2	0.2%
3/7/2000	2	0.2%
12/26/1966	2	0.2%
12/11/2000	2	0.2%
Other values (781)	787	97.5%

Most occurring characters

Value	Count	Frequency (%)
/	1604	22.2%
1	1573	21.8%
9	1170	16.2%
2	559	7.7%
8	426	5.9%
6	419	5.8%
7	381	5.3%
5	313	4.3%
0	280	3.9%
3	253	3.5%
Other values (13)	244	3.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7222	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
/	1604	22.2%
1	1573	21.8%
9	1170	16.2%
2	559	7.7%
8	426	5.9%
6	419	5.8%
7	381	5.3%
5	313	4.3%
0	280	3.9%
3	253	3.5%
Other values (13)	244	3.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7222	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
/	1604	22.2%
1	1573	21.8%
9	1170	16.2%
2	559	7.7%
8	426	5.9%
6	419	5.8%
7	381	5.3%
5	313	4.3%
0	280	3.9%
3	253	3.5%
Other values (13)	244	3.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7222	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
/	1604	22.2%
1	1573	21.8%
9	1170	16.2%
2	559	7.7%
8	426	5.9%
6	419	5.8%
7	381	5.3%
5	313	4.3%
0	280	3.9%
3	253	3.5%
Other values (13)	244	3.4%

salary
Real number (ℝ)

Missing

Distinct	932
Distinct (%)	100.0%
Missing	68
Missing (%)	6.8%
Infinite	0
Infinite (%)	0.0%
Mean	149005.36

Minimum	12380.49
Maximum	286592.99
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	12380.49
5-th percentile	26500.177
Q1	81559.717
median	147274.52
Q3	220103.46
95-th percentile	274961.32
Maximum	286592.99
Range	274212.5
Interquartile range (IQR)	138543.75

Descriptive statistics

Standard deviation	79785.177
Coefficient of variation (CV)	0.53545173
Kurtosis	-1.2105125
Mean	149005.36
Median Absolute Deviation (MAD)	68183.345
Skewness	0.039327608
Sum	1.3887299 × 10⁸
Variance	6.3656744 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
38292.37	1	0.1%
57194.86	1	0.1%
123903.42	1	0.1%
230451.15	1	0.1%
69227.11	1	0.1%
14247.62	1	0.1%
186469.43	1	0.1%
231067.84	1	0.1%
27234.28	1	0.1%
210001.95	1	0.1%
Other values (922)	922	92.2%
(Missing)	68	6.8%

Value	Count	Frequency (%)
12380.49	1	0.1%
12834.8	1	0.1%
13268.99	1	0.1%
13375.17	1	0.1%
13574.77	1	0.1%
13673.35	1	0.1%
14247.62	1	0.1%
14673.04	1	0.1%
15270.86	1	0.1%
15423.09	1	0.1%

Value	Count	Frequency (%)
286592.99	1	0.1%
286061.25	1	0.1%
285036.95	1	0.1%
284737.57	1	0.1%
284728.99	1	0.1%
284608.82	1	0.1%
284300.15	1	0.1%
284062.49	1	0.1%
283771.86	1	0.1%
283517.64	1	0.1%

title
Text

Distinct	182
Distinct (%)	18.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	36
Median length	26
Mean length	14.637
Min length	0

Characters and Unicode

Total characters	14637
Distinct characters	53
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	34 ?
Unique (%)	3.4%

Sample

1st row	Internal Auditor
2nd row	Accountant IV
3rd row	Structural Engineer
4th row	Senior Cost Accountant
5th row

Value	Count	Frequency (%)
engineer	120	6.4%
assistant	64	3.4%
analyst	59	3.1%
manager	58	3.1%
senior	51	2.7%
i	50	2.6%
ii	48	2.5%
iv	47	2.5%
iii	45	2.4%
accountant	40	2.1%
Other values (118)	1306	69.2%

Most occurring characters

Value	Count	Frequency (%)
e	1384	9.5%
t	1122	7.7%
n	1119	7.6%
a	1091	7.5%
	1085	7.4%
i	1056	7.2%
r	937	6.4%
s	832	5.7%
c	686	4.7%
o	684	4.7%
Other values (43)	4641	31.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	14637	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1384	9.5%
t	1122	7.7%
n	1119	7.6%
a	1091	7.5%
	1085	7.4%
i	1056	7.2%
r	937	6.4%
s	832	5.7%
c	686	4.7%
o	684	4.7%
Other values (43)	4641	31.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	14637	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1384	9.5%
t	1122	7.7%
n	1119	7.6%
a	1091	7.5%
	1085	7.4%
i	1056	7.2%
r	937	6.4%
s	832	5.7%
c	686	4.7%
o	684	4.7%
Other values (43)	4641	31.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	14637	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1384	9.5%
t	1122	7.7%
n	1119	7.6%
a	1091	7.5%
	1085	7.4%
i	1056	7.2%
r	937	6.4%
s	832	5.7%
c	686	4.7%
o	684	4.7%
Other values (43)	4641	31.7%

comments
Text

Distinct	84
Distinct (%)	8.5%
Missing	6
Missing (%)	0.6%
Memory size	7.9 KiB

Length

Max length	217
Median length	0
Mean length	4.1338028
Min length	0

Characters and Unicode

Total characters	4109
Distinct characters	394
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	25 ?
Unique (%)	2.5%

Sample

1st row	1E+02
2nd row
3rd row
4th row
5th row

Value	Count	Frequency (%)
	39	8.7%
1.00	9	2.0%
touch	9	2.0%
1e+02	7	1.6%
1e2	7	1.6%
etc/hosts	5	1.1%
💔	5	1.1%
💓	5	1.1%
💗	5	1.1%
💖	5	1.1%
Other values (149)	354	78.7%

Most occurring characters

Value	Count	Frequency (%)
	274	6.7%
.	209	5.1%
/	135	3.3%
9	98	2.4%
t	87	2.1%
s	86	2.1%
e	80	1.9%
o	67	1.6%
l	65	1.6%
h	56	1.4%
Other values (384)	2952	71.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4109	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	274	6.7%
.	209	5.1%
/	135	3.3%
9	98	2.4%
t	87	2.1%
s	86	2.1%
e	80	1.9%
o	67	1.6%
l	65	1.6%
h	56	1.4%
Other values (384)	2952	71.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4109	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	274	6.7%
.	209	5.1%
/	135	3.3%
9	98	2.4%
t	87	2.1%
s	86	2.1%
e	80	1.9%
o	67	1.6%
l	65	1.6%
h	56	1.4%
Other values (384)	2952	71.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4109	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	274	6.7%
.	209	5.1%
/	135	3.3%
9	98	2.4%
t	87	2.1%
s	86	2.1%
e	80	1.9%
o	67	1.6%
l	65	1.6%
h	56	1.4%
Other values (384)	2952	71.8%

	gender	id	salary
gender	1.000	0.038	0.098
id	0.038	1.000	0.002
salary	0.098	0.002	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

	registration_dttm	id	first_name	last_name	email	gender	ip_address	cc	country	birthdate	salary	title	comments
0	2016-02-03 07:55:29	1	Amanda	Jordan	ajordan0@com.com	Female	1.197.201.2	6759521864920116	Indonesia	3/8/1971	49756.53	Internal Auditor	1E+02
1	2016-02-03 17:04:03	2	Albert	Freeman	afreeman1@is.gd	Male	218.111.175.34		Canada	1/16/1968	150280.17	Accountant IV
2	2016-02-03 01:09:31	3	Evelyn	Morgan	emorgan2@altervista.org	Female	7.161.136.94	6767119071901597	Russia	2/1/1960	144972.51	Structural Engineer
3	2016-02-03 00:36:21	4	Denise	Riley	driley3@gmpg.org	Female	140.35.109.83	3576031598965625	China	4/8/1997	90263.05	Senior Cost Accountant
4	2016-02-03 05:05:31	5	Carlos	Burns	cburns4@miitbeian.gov.cn		169.113.235.40	5602256255204850	South Africa		NaN
5	2016-02-03 07:22:34	6	Kathryn	White	kwhite5@google.com	Female	195.131.81.179	3583136326049310	Indonesia	2/25/1983	69227.11	Account Executive
6	2016-02-03 08:33:08	7	Samuel	Holmes	sholmes6@foxnews.com	Male	232.234.81.197	3582641366974690	Portugal	12/18/1987	14247.62	Senior Financial Analyst
7	2016-02-03 06:47:06	8	Harry	Howell	hhowell7@eepurl.com	Male	91.235.51.73		Bosnia and Herzegovina	3/1/1962	186469.43	Web Developer IV
8	2016-02-03 03:52:53	9	Jose	Foster	jfoster8@yelp.com	Male	132.31.53.61		South Korea	3/27/1992	231067.84	Software Test Engineer I	1E+02
9	2016-02-03 18:29:47	10	Emily	Stewart	estewart9@opensource.org	Female	143.28.251.245	3574254110301671	Nigeria	1/28/1997	27234.28	Health Coach IV

	registration_dttm	id	first_name	last_name	email	gender	ip_address	cc	country	birthdate	salary	title
990	2016-02-03 20:31:10	991	Russell	Hunt	rhuntri@yahoo.co.jp	Male	216.75.221.150	3528271233562473	Canada	6/8/1970	124353.04	GIS Technical Architect
991	2016-02-03 08:35:53	992	Martha	Howard	mhowardrj@cdc.gov	Female	158.184.80.14	3566576585892705	Poland	7/18/2000	158522.84	Paralegal
992	2016-02-03 11:48:54	993	Patricia	Henderson	phendersonrk@delicious.com	Female	4.2.237.115	4041374756559	Indonesia	2/16/1960	166651.78	Programmer Analyst IV
993	2016-02-03 01:14:13	994	Carol	Williams	cwilliamsrl@army.mil	Female	53.242.60.20		France	1/5/1988	120933.54	Recruiter
994	2016-02-03 00:18:26	995	Jose	Mccoy	jmccoyrm@elpais.com	Male	117.37.215.98	560222933605513180	Norway	7/30/1987	275898.37	Graphic Designer
995	2016-02-03 10:30:59	996	Dennis	Harris	dharrisrn@eepurl.com	Male	178.180.111.236	374288806662929	Greece	7/8/1965	263399.54	Editor
996	2016-02-03 17:16:53	997	Gloria	Hamilton	ghamiltonro@rambler.ru	Female	71.50.39.137		China	4/22/1975	83183.54	VP Product Management
997	2016-02-03 05:02:20	998	Nancy	Morris	nmorrisrp@ask.com		6.188.121.221	3553564071014997	Sweden	5/1/1979	NaN	Junior Executive
998	2016-02-03 02:41:32	999	Annie	Daniels	adanielsrq@squidoo.com	Female	97.221.132.35	30424803513734	China	10/9/1991	18433.85	Editor
999	2016-02-03 09:52:18	1000	Julie	Meyer	jmeyerrr@flavors.me	Female	217.1.147.132	374288099198540	China		222561.13

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts